Advances in Thymoma Imaging

Thymic Carcinoma Invading Bilateral Internal Thoracic Artery Bypass Grafts: Diffuse Stenosis Suggesting Extravascular Compression

Thymic carcinoma, a rare but aggressively growing malignancy that tends to invade nearby structures, requires early intervention and is often associated with poor prognosis. A 73-year-old man presented with vague chest pain. Imaging studies coincidently revealed an anterior mediastinal mass invading bilateral internal thoracic artery bypass grafts. Angiography showed diffuse stenosis due to tumor compression and numerous feeding arteries. Positron emission tomography scans led to the clinical diagnosis of thymic carcinoma, stage IVb. We reported an extremely rare and complicated case of unresectable thymic carcinoma invading coronary artery bypass grafts, aiming to discuss the complex features challenging the diagnostic approach and management of the disease. Diffuse stenosis on angiography may suggest extravascular compression by coincident mediastinal tumors. Complicated cases of mediastinal neoplasm with invasion of vital structures require individualized diagnostic approaches and treatment strategies.

Using optimized CT type to predict histological classifications of thymic epithelial tumors: a radiomics integrated analysis

OBJECTIVE

To develop and externally validate an integrated model that utilizes optimized radiomics features from non-contrast-enhanced CT (NE-CT) or contrast-enhanced CT (CE-CT), along with morphological features and clinical risk factors, to predict histological classifications of thymic epithelial tumors (TETs).

METHODS

A total of 182 patients with TET, classified as the low-risk group and the high-risk group based on histology, were divided into a training cohort (N = 122, center 1) and an external validation cohort (N = 60, center 2). Radiomics features were extracted from different CT types, followed by feature selection, including consistency, correlation, and importance tests, to generate Rad-scores for both NE-CT and CE-CT. The integrated model was developed by combining the optimal Rad-score, morphological features, and clinical risk factors using multivariate logistic regression. Model performance was assessed by the area under the receiver operating characteristic curve (AUC) and compared by Delong test. A nomogram was used to visually present the integrated model.

RESULTS

A total of 851 radiomics features were extracted, with NE-CT and CE-CT Rad-scores consisting of four and five features, respectively. The AUCs of the CE-CT Rad-score were higher than those of the NE-CT Rad-score in both the training cohort (0.783 vs 0.749) and the external validation cohort (0.775 vs 0.723, p = 0.361). The integrated model, combining five morphological features and the CE-CT Rad-score, achieved AUCs of 0.814 and 0.802 in the training and external validation cohorts, respectively.

CONCLUSION

The integrated model, incorporating radiomics features from CE-CT and morphological features, can help to identify the histological classifications of TETs.

CRITICAL RELEVANCE STATEMENT

This study developed an integrated model based on radiomics features from contrast-enhanced CT and morphological features, demonstrating that the integrated model has impressive predictive capability in distinguishing histological classifications of thymic epithelial tumors through external validation.

KEY POINTS

Radiomics features extracted from CT more effectively represented thymic epithelial tumor (TET) heterogeneity than morphological features. The radiomics model using contrast-enhanced CT outperformed that using non-contrast-enhanced CT in identifying histological classifications of TET. The integrated model, combining radiomics and morphological features, exhibited the highest performance in predicting TET histological classifications.

Computed tomography radiomics-based combined model for predicting thymoma risk subgroups: a multicenter retrospective study

RATIONALE AND OBJECTIVES

Accurately distinguishing histological subtypes and risk categorization of thymomas is difficult. To differentiate the histologic risk categories of thymomas, we developed a combined radiomics model based on non-enhanced and contrast-enhanced computed tomography (CT) radiomics, clinical, and semantic features.

MATERIALS AND METHODS

In total, 360 patients with pathologically-confirmed thymomas who underwent CT examinations were retrospectively recruited from three centers. Patients were classified using improved pathological classification criteria as low-risk (LRT: types A and AB) or high-risk (HRT: types B1, B2, and B3). The training and external validation sets comprised 274 (from centers 1 and 2) and 86 (center 3) patients, respectively. A clinical-semantic model was built using clinical and semantic variables. Radiomics features were filtered using intraclass correlation coefficients, correlation analysis, and univariate logistic regression. An optimal radiomics model (Rad_score) was constructed using the AutoML algorithm, while a combined model was constructed by integrating Rad_score with clinical and semantic features. The predictive and clinical performances of the models were evaluated using receiver operating characteristic/calibration curve analyses and decision-curve analysis, respectively.

RESULTS

Radiomics and combined models (area under curve: training set, 0.867 and 0.884; external validation set, 0.792 and 0.766, respectively) exhibited performance superior to the clinical-semantic model. The combined model had higher accuracy than the radiomics model (0.79 vs. 0.78, p<0.001) in the entire cohort. The original_firstorder_median of venous phase had the highest relative importance among features in the radiomics model.

CONCLUSION

Radiomics and combined radiomics models may serve as noninvasive discrimination tools to differentiate thymoma risk classifications.

Risk stratification of thymic epithelial tumors based on peritumor CT radiomics and semantic features

OBJECTIVES

To develop and validate nomograms combining radiomics and semantic features to identify the invasiveness and histopathological risk stratification of thymic epithelial tumors (TET) using contrast-enhanced CT.

METHODS

This retrospective multi-center study included 224 consecutive cases. For each case, 6764 intratumor and peritumor radiomics features and 31 semantic features were collected. Multi-feature selections and decision tree models were performed on radiomics features and semantic features separately to select the most important features for Masaoka-Koga staging and WHO classification. The selected features were then combined to create nomograms for the two systems. The performance of the radiomics model, semantic model, and combined model was evaluated using the area under the receiver operating characteristic curves (AUCs).

RESULTS

One hundred eighty-seven cases (56.5 years ± 12.3, 101 men) were included, with 62 cases as the external test set. For Masaoka-Koga staging, the combined model, which incorporated five peritumor radiomics features and four semantic features, showed an AUC of 0.958 (95% CI: 0.912-1.000) in distinguishing between early-stage (stage I/II) and advanced-stage (III/IV) TET in the external test set. For WHO classification, the combined model incorporating five peritumor radiomics features and two semantic features showed an AUC of 0.857 (0.760-0.955) in differentiating low-risk (type A/AB/B1) and high-risk (B2/B3/C) TET. The combined models showed the most effective predictive performance, while the semantic models exhibited comparable performance to the radiomics models in both systems (p > 0.05).

CONCLUSION

The nomograms combining peritumor radiomics features and semantic features could help in increasing the accuracy of grading invasiveness and risk stratification of TET.

CRITICAL RELEVANCE STATEMENT

Peripheral invasion and histopathological type are major determinants of treatment and prognosis of TET. The integration of peritumoral radiomics features and semantic features into nomograms may enhance the accuracy of grading invasiveness and risk stratification of TET.

KEY POINTS

Peritumor region of TET may suggest histopathological and invasive risk. Peritumor radiomic and semantic features allow classification by Masaoka-Koga staging (AUC: 0.958). Peritumor radiomic and semantic features enable the classification of histopathological risk (AUC: 0.857).

Cine-MRI and T1TSE Sequence for Mediastinal Mass

Background/Objectives: Contrast-enhanced computed tomography (CT) is the standard radiologic examination for evaluating the extent of mediastinal tumors. If tumor infiltration into the large central thoracic vessels, the pericardium, or the myocardium is suspected, cine magnetic resonance imaging (cine-MRI) can provide additional valuable information. Methods: We conducted a retrospective study of patients with mediastinal tumors who were staged with CT, cine-MRI, and a T1-weighted turbo spin echo (T1TSE) prior to surgical resection. Imaging was re-evaluated regarding tumor infiltration into the pericardium, myocardium, superior vena cava, aorta, pulmonary arteries, and atria and compared with intraoperative findings and postoperative histopathological reports (gold standard). Unclear CT findings were further investigated. Results: Forty-seven patients (29 female and 18 male patients; median age: 58 years) met the inclusion criteria. Cine-MRI was able to predict infiltration of the aorta in 86%, pulmonary arteries in 85%, and atria in 80% of unclear CT cases. Aortic tumor infiltration in unclear CT cases was significantly more often correctly diagnosed with cine-MRI than with T1TSE sequence. Conclusions: Additional cine-MRI is of crucial benefit in unclear CT cases. We recommend performing cine-MRI if infiltration into the large central vessels and atria is suspected. T1TSE sequence is of very limited additional value.

Thymic Imaging Pitfalls and Strategies for Optimized Diagnosis

Thymic imaging is challenging because the imaging appearance of a variety of benign and malignant thymic conditions are similar. CT is the most commonly used modality for mediastinal imaging, while MRI and fluorine 18 fluorodeoxyglucose (FDG) PET/CT are helpful when they are tailored to the correct indication. Each of these imaging modalities has limitations and technical pitfalls that may lead to an incorrect diagnosis and mismanagement. CT may not be sufficient for the characterization of cystic thymic processes and differentiation between thymic hyperplasia and thymic tumors. MRI can be used to overcome these limitations but is subject to other potential pitfalls such as an equivocal decrease in signal intensity at chemical shift imaging, size limitations, unusual signal intensity for cysts, subtraction artifacts, pseudonodularity on T2-weighted MR images, early imaging misinterpretation, flow and spatial resolution issues hampering assessment of local invasion, and the overlap of apparent diffusion coefficients between malignant and benign thymic entities. FDG PET/CT is not routinely indicated due to some overlap in FDG uptake between thymomas and benign thymic processes. However, it is useful for staging and follow-up of aggressive tumors (eg, thymic carcinoma), particularly for detection of occult metastatic disease. Pitfalls in imaging after treatment of thymic malignancies relate to technical challenges such as postthymectomy sternotomy streak metal artifacts, differentiation of postsurgical thymic bed changes from tumor recurrence, or human error with typical "blind spots" for identification of metastatic disease. Understanding these pitfalls enables appropriate selection of imaging modalities, improves diagnostic accuracy, and guides patient treatment. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Multimodal modeling with low-dose CT and clinical information for diagnostic artificial intelligence on mediastinal tumors: a preliminary study

BACKGROUND

Diagnosing mediastinal tumours, including incidental lesions, using low-dose CT (LDCT) performed for lung cancer screening, is challenging. It often requires additional invasive and costly tests for proper characterisation and surgical planning. This indicates the need for a more efficient and patient-centred approach, suggesting a gap in the existing diagnostic methods and the potential for artificial intelligence technologies to address this gap. This study aimed to create a multimodal hybrid transformer model using the Vision Transformer that leverages LDCT features and clinical data to improve surgical decision-making for patients with incidentally detected mediastinal tumours.

METHODS

This retrospective study analysed patients with mediastinal tumours between 2010 and 2021. Patients eligible for surgery (n=30) were considered 'positive,' whereas those without tumour enlargement (n=32) were considered 'negative.' We developed a hybrid model combining a convolutional neural network with a transformer to integrate imaging and clinical data. The dataset was split in a 5:3:2 ratio for training, validation and testing. The model's efficacy was evaluated using a receiver operating characteristic (ROC) analysis across 25 iterations of random assignments and compared against conventional radiomics models and models excluding clinical data.

RESULTS

The multimodal hybrid model demonstrated a mean area under the curve (AUC) of 0.90, significantly outperforming the non-clinical data model (AUC=0.86, p=0.04) and radiomics models (random forest AUC=0.81, p=0.008; logistic regression AUC=0.77, p=0.004).

CONCLUSION

Integrating clinical and LDCT data using a hybrid transformer model can improve surgical decision-making for mediastinal tumours, showing superiority over models lacking clinical data integration.

Spontaneous rupture‑induced life‑threatening mediastinal mixed germ cell tumor: A case report and therapeutic considerations

Spontaneous rupture and hemorrhage of mediastinal germ cell tumors is a rare occurrence. In the current report, the case of a 20-year-old male patient who was admitted with chest tightness and dyspnea is presented. An urgent chest CT scan revealed a large tumor in the right anterior mediastinum, measuring ~12 cm in diameter, with associated intratumoral hemorrhage. An emergency thoracotomy was performed to excise the lesion, which revealed that the bleeding was caused by a ruptured tumor. Postoperative pathological findings revealed a mediastinal mixed germ cell tumor consisting of four pathological types: Embryonal carcinoma, seminoma, yolk sac tumor and immature teratoma. Postoperatively, the patient showed marked improvement in the symptoms of dyspnea. However, the follow-up outcome was poor, and the patient succumbed 2 months after surgery. To the best of our knowledge, there are no reports of rupture and hemorrhage involving >4 mixed germ cell tumors. In the present report, the experience of the treatment of the patient is summarized, and literature was reviewed to improve clinicians' awareness of the disease.

Extracellular volume fraction derived from equilibrium contrast-enhanced CT as a diagnostic parameter in anterior mediastinal tumors

PURPOSE

To assess the usefulness of extracellular volume (ECV) fraction derived from equilibrium contrast-enhanced CT (CECT) for diagnosing anterior mediastinal tumors.

METHOD

This study included 161 histologically confirmed anterior mediastinal tumors (55 low-risk thymomas, 57 high-risk thymomas, 32 thymic carcinomas, and 17 malignant lymphomas) that were assessed by pretreatment CECT. ECV fraction was calculated using measurements obtained within the lesion and the aorta on unenhanced and equilibrium phase CECT. ECV fraction was compared among anterior mediastinal tumors using one-way ANOVA or t-test. Receiver-operating characteristic (ROC) curve analysis was performed to evaluate the ability of ECV fraction to differentiate thymic carcinomas/lymphomas from thymomas.

RESULTS

ECV fraction differed significantly among the anterior mediastinal tumors (p < 0.001). ECV fraction of thymic carcinomas was significantly higher than those of low-risk thymomas, high-risk thymomas, and lymphomas (p < 0.001, p < 0.001, and p = 0.006, respectively). ECV fraction of lymphomas was significantly higher than that of low-risk thymomas (p < 0.001). ECV fraction was significantly higher in thymic carcinomas/lymphomas than in thymomas (40.1 % vs. 27.7 %, p < 0.001). The optimal cutoff value to differentiate thymic carcinomas/lymphomas from thymomas was 38.5 % (AUC, 0.805; 95 %CI, 0.736-0.863).

CONCLUSIONS

ECV fraction derived from equilibrium CECT is helpful in diagnosing anterior mediastinal tumors. High ECV fraction is indicative of thymic carcinomas/lymphomas, particularly thymic carcinomas.

MG-Net: Multi-level global-aware network for thymoma segmentation

BACKGROUND AND OBJECTIVE

Automatic thymoma segmentation in preoperative contrast-enhanced computed tomography (CECT) images makes great sense for diagnosis. Although convolutional neural networks (CNNs) are distinguished in medical image segmentation, they are challenged by thymomas with various shapes, scales and textures, owing to the intrinsic locality of convolution operations. In order to overcome this deficit, we built a deep learning network with enhanced global-awareness for thymoma segmentation.

METHODS

We propose a multi-level global-aware network (MG-Net) for thymoma segmentation, in which the multi-level feature interaction and integration are jointly designed to enhance the global-awareness of CNNs. Particularly, we design the cross-attention block (CAB) to calculate pixel-wise interactions of multi-level features, resulting in the Global Enhanced Convolution Block, which can enable the network to handle various thymomas by strengthening the global-awareness of the encoder. We further devise the Global Spatial Attention Module to integrate coarse- and fine-grain information for enhancing the semantic consistency between the encoder and decoder with CABs. We also develop an Adaptive Attention Fusion Module to adaptively aggregate different semantic-scale features in the decoder to preserve comprehensive details.

RESULTS

The MG-Net has been evaluated against several state-of-the-art models on the self-collected CECT dataset and NIH Pancreas-CT dataset. Results suggest that all designed components are effective, and MG-Net has superior segmentation performance and generalization ability over existing models.

CONCLUSION

Both the qualitative and quantitative experimental results indicate that our MG-Net with global-aware ability can achieve accurate thymoma segmentation and has generalization ability in different tasks. The code is available at: https://github.com/Leejyuan/MGNet.

Feasibility of iodine concentration and extracellular volume fraction measurement derived from the equilibrium phase dual-energy CT for differentiating thymic epithelial tumors

PURPOSE

To assess the diagnostic feasibility of iodine concentration (IC) and extracellular volume (ECV) fraction measurement using the equilibrium phase dual-energy CT (DECT) for the evaluation of thymic epithelial tumors (TETs).

MATERIALS AND METHODS

This study included 33 TETs (11 low-risk thymomas, 11 high-risk thymomas, and 11 thymic carcinomas) that were assessed by pretreatment DECT. IC was measured during the equilibrium phases and ECV fraction was calculated using IC of the thymic lesion and the aorta. IC and ECV fraction were compared among TET subtypes using the Kruskal-Wallis H test and Mann-Whitney U test. Receiver-operating characteristic (ROC) curve analysis was performed to evaluate the ability of IC and ECV fraction to diagnose thymic carcinoma.

RESULTS

IC during the equilibrium phase and ECV fraction differed among the three TET groups (both p < 0.001). IC during the equilibrium phase and ECV fraction was significantly higher in thymic carcinomas than in thymomas (1.9 mg/mL vs. 1.2 mg/mL, p < 0.001; 38.2% vs. 25.9%, p < 0.001; respectively). The optimal cutoff values of IC during the equilibrium phase and of ECV fraction to diagnose thymic carcinoma were 1.5 mg/mL (AUC, 0.955; sensitivity, 100%; specificity, 90.9%) and 26.8% (AUC, 0.888; sensitivity, 100%; specificity, 72.7%), respectively.

CONCLUSION

IC and ECV fraction measurement using DECT are helpful in diagnosing TETs. High IC during the equilibrium phase and high ECV fraction are suggestive of thymic carcinoma.

Utility of non-contrast-enhanced magnetic resonance imaging in predicting preoperative clinical stage and prognosis in patients with thymic epithelial tumor

PURPOSE

The purpose of this study was to find useful imaging features on non-contrast-enhanced magnetic resonance imaging (MRI) that can divide patients with thymic epithelial tumor (TET) into clinical stage I-II and III-IV groups under assumption that contrast media are contraindicated.

MATERIALS AND METHODS

This retrospective study included 106 patients (median age, 60 years; range, 27-82 years; 62 women) with surgically resected TET who underwent MRI between August 1986 and July 2015. All cases were classified according to the 2015 WHO classification and staged using the eighth edition of the TNM system. Two radiologists independently evaluated 14 categories of MRI findings; the findings in patients with stage I-II were compared with those of patients with stage III-IV using a logistic regression model. Disease-specific survival associated with significant findings was calculated using the Kaplan-Meier method.

RESULTS

Univariate analysis showed that stage III-IV patients were more likely to have tumors with an irregular contour, heterogeneity on T1WI, low-signal intensity on T2WI, irregular border with lung, findings of great vessel invasion (GVI) (hereafter, GVI sign), pericardial thickening/nodule, and lymphadenopathy (all, P < 0.01). On multivariable analysis, only two findings, irregular border between tumor and lung (odds ratio [OR], 272.8; 95% CI 26.6-2794.1; P < 0.001) and positive GVI sign (OR, 49.3; 95% CI 4.5-539.8; P = 0.001) remained statistically significant. Patients with one or both features had significantly worse survival (log-rank test, P < 0.001).

CONCLUSION

For patients with TET who are unable to receive contrast for preoperative staging, the two image findings of an irregular border between tumor and lung and the positive GVI sign on non-contrast-enhanced MRI could be helpful in determining stage III-IV disease which is associated with a worse survival.

Machine-learning classifiers based on non-enhanced computed tomography radiomics to differentiate anterior mediastinal cysts from thymomas and low-risk from high-risk thymomas: A multi-center study

Background

This study aimed to investigate the diagnostic value of machine-learning (ML) models with multiple classifiers based on non-enhanced CT Radiomics features for differentiating anterior mediastinal cysts (AMCs) from thymomas, and high-risk from low risk thymomas.

Methods

In total, 201 patients with AMCs and thymomas from three centers were included and divided into two groups: AMCs vs. thymomas, and high-risk vs low-risk thymomas. A radiomics model (RM) was built with 73 radiomics features that were extracted from the three-dimensional images of each patient. A combined model (CM) was built with clinical features and subjective CT finding features combined with radiomics features. For the RM and CM in each group, five selection methods were adopted to select suitable features for the classifier, and seven ML classifiers were employed to build discriminative models. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of each combination.

Results

Several classifiers combined with suitable selection methods demonstrated good diagnostic performance with areas under the curves (AUCs) of 0.876 and 0.922 for the RM and CM in group 1 and 0.747 and 0.783 for the RM and CM in group 2, respectively. The combination of support vector machine (SVM) as the feature-selection method and Gradient Boosting Decision Tree (GBDT) as the classification algorithm represented the best comprehensive discriminative ability in both group. Comparatively, assessments by radiologists achieved a middle AUCs of 0.656 and 0.626 in the two groups, which were lower than the AUCs of the RM and CM. Most CMs exhibited higher AUC value compared to RMs in both groups, among them only a few CMs demonstrated better performance with significant difference in group 1.

Conclusion

Our ML models demonstrated good performance for differentiation of AMCs from thymomas and low-risk from high-risk thymomas. ML based on non-enhanced CT radiomics may serve as a novel preoperative tool.

Contrast-enhanced CT-based radiomics model for differentiating risk subgroups of thymic epithelial tumors

Background

To validate a contrast-enhanced CT (CECT)-based radiomics model (RM) for differentiating various risk subgroups of thymic epithelial tumors (TETs).

Methods

A retrospective study was performed on 164 patients with TETs who underwent CECT scans before treatment. A total of 130 patients (approximately 79%, from 2012 to 2018) were designated as the training set, and 34 patients (approximately 21%, from 2019 to 2021) were designated as the testing set. The analysis of variance and least absolute shrinkage and selection operator algorithm methods were used to select the radiomics features. A logistic regression classifier was constructed to identify various subgroups of TETs. The predictive performance of RMs was evaluated based on receiver operating characteristic (ROC) curve analyses.

Results

Two RMs included 16 and 13 radiomics features to identify three risk subgroups of traditional risk grouping [low-risk thymomas (LRT: Types A, AB and B1), high-risk thymomas (HRT: Types B2 and B3), thymic carcinoma (TC)] and improved risk grouping [LRT* (Types A and AB), HRT* (Types B1, B2 and B3), TC], respectively. For traditional risk grouping, the areas under the ROC curves (AUCs) of LRT, HRT, and TC were 0.795, 0.851, and 0.860, respectively, the accuracy was 0.65 in the training set, the AUCs were 0.621, 0.754, and 0.500, respectively, and the accuracy was 0.47 in the testing set. For improved risk grouping, the AUCs of LRT*, HRT*, and TC were 0.855, 0.862, and 0.869, respectively, and the accuracy was 0.72 in the training set; the AUCs were 0.778, 0.716, and 0.879, respectively, and the accuracy was 0.62 in the testing set.

Conclusions

CECT-based RMs help to differentiate three risk subgroups of TETs, and RM established according to improved risk grouping performed better than traditional risk grouping.

Comparison of Interobserver Agreement and Diagnostic Accuracy for IASLC/ITMIG Thymic Epithelial Tumor Staging Among Co-registered FDG-PET/MRI, Whole-body MRI, Integrated FDG-PET/CT, and Conventional Imaging Examination with and without Contrast Media Administrations

RATIONALE AND OBJECTIVES

The purpose of this study was to compare the interobserver agreements and diagnostic accuracies for IASLC/ITMIG (International Association for the Study of Lung Cancer/International Thymic Malignancies Interest Group) thymic epithelial tumor staging of co-registered fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (FDG-PET/MRI), MRI, integrated fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT), and conventional imaging examination.

MATERIALS AND METHODS

Prospective whole-body MRI including diffusion-weighted imaging, integrated PET/CTs, conventional imaging examinations, pathological examinations, and surgical reports, as well as follow-up examinations, were performed for 64 consecutive patients with thymic epithelial tumor. All FDG-PET/MRIs were co-registered PET data with MRI. TNM staging was evaluated by two radiologists on the basis of the IASLC/ITMIG thymic epithelial tumor staging system. Kappa statistics were determined for evaluations of agreements of all factors between each of the methods and final diagnosis. Finally, the diagnostic accuracy of each factor and of determination of the clinical stage was statistically compared to each other using McNemar test.

RESULTS

Agreements for all factors between each method and final diagnosis were assessed as fair, moderate, substantial, or almost perfect (0.28 ≤ kappa value ≤ 0.80; P < .0001). Diagnostic accuracy for N factor of PET/MRI (93.8% [60/64]) and MRI (93.8% [60/64]) was significantly higher than that of conventional imaging examination (81.3% [52/64] vs PET/MRI and MRI; P = .008). In addition, diagnostic accuracy for staging of PET/MRI (84.4% [54/64]) and MRI (84.4 [54/64]) was significantly higher than that of conventional imaging examination (71.9% [46/64] vs PET/MRI and MRI; P = .008).

CONCLUSIONS

Whole-body PET/MRI, MRI, and PET/CT have better interobserver agreements and accuracies than conventional imaging examination for the new IASLC/ITMIG thymic epithelial tumor staging.

Using CT to evaluate mediastinal great vein invasion by thymic epithelial tumors: measurement of the interface between the tumor and neighboring structures

OBJECTIVES

For thymic epithelial tumors, simple contact with adjacent structures does not necessarily mean invasion. The purpose of our study was to develop a simple noninvasive technique for evaluating organ invasion using routine pretreatment computed tomography (CT).

METHODS

This retrospective study analyzed the pathological reports on 95 mediastinal resections performed between January 2003 and June 2020. Using CT images, the length of the interface between the primary tumor and neighboring structures (arch distance; Adist) and maximum tumor diameter (Dmax) was measured, after which Adist/Dmax (A/D) ratios were calculated. Receiver operating characteristic (ROC) curves were used to analyze the Adist and A/D ratios.

RESULTS

An Adist cut-off of 37.5 mm best distinguished between invaded and non-invaded mediastinal great veins based on ROC curves. When Adist > 37.5 mm was used for diagnosis of invasion of the brachiocephalic vein (BCV) or superior vena cava (SVC), the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the ROC curve for diagnosis of invasion were 61.9%, 92.5%, 81.25%, 82.2%, 81.97%, and 0.76429, respectively. Moreover, there were significant differences between BCV/SVC Adist > 37.5 mm and ≤ 37.5 mm for 10-year relapse-free survival and 10-year overall survival (p < 0.01).

CONCLUSIONS

When diagnosing invasion of the mediastinal great veins based on Adist > 37.5 mm, we achieved a higher performance level than the conventional criteria such as irregular interface with an absence of the fat layer. Measurement of Adist is a simple noninvasive technique for evaluating invasion using CT. Key Points • Simple contact between the primary tumor and adjacent structures on CT does not indicate direct invasion. • Using CT images, the length of the interface between the primary tumor and neighboring structures (arch distance; Adist) is a simple noninvasive technique for evaluating invasion. • Adist > 37.5 mm can be a supportive tool to identify invaded mediastinal great veins and surgical indications for T3 and T4 invasion by thymic epithelial tumors.

[Mediastinal Tumors]

If mediastinal tumours cause symptoms these are related to their anatomical localization or a paraneoplastic syndrome. The differential diagnosis is based on the clinical situation with finding the lesion, and, furthermore, taking into account the age and sex of the patient, and the mediastinal compartment where the lesion is located. Cross-sectional radiographic diagnostic is essential for defining the therapeutic strategy. The anterior mediastinum is dominated by thymic tumours, mediastinal lymphomas, germ cell tumours and ectopic mediastinal poiters. The middle mediastinal compartment is the most frequent place of mediastinal cystic tumours, whereas the posterior mediastinum is the domain of neurogenic tumours. For selected cases a tissue biopsy is required. Surgery is the mainstay for most mediastinal tumours. Median sternotomy is the most frequent conventional surgical technique while minimally invasive surgery with thoracoscopic and above all robot assisted operation techniques are increasingly frequent. Combined chemotherapy and modern radiotherapy are essential components of the comprehensive treatment for mediastinal tumours.

CT texture analysis in evaluation of thymic tumors and thymic hyperplasia: correlation with the international thymic malignancy interest group (ITMIG) stage and WHO grade

OBJECTIVES

To evaluate the effectiveness of CT texture analysis (CTTA) in (1) differentiating Thymoma (THY) from thymic hyperplasia (TH) (2) low from high WHO grade, and (3) low from high Masaoka Koga (MK)/International Thymic Malignancy Interest Group (ITMIG) stages.

METHODS

After institute ethical clearance, this cross-sectional study analyzed 26 patients (THY-18, TH-8) who underwent dual energy CT (DECT) and surgery between January 2016 and December 2018. CTTA was performed using TexRad (Feedback Medical Ltd., Cambridge, UK- www.fbkmed.com) by a single observer. Free hand regions of interest (ROIs) were placed over axial sections where there was maximum enhancement and homogeneity. Filtration histogram was used to generate six first-order texture parameters [mean, standard deviation (SD), mean of positive pixels (MPP), entropy, skewness, and kurtosis] at six spatial scaling factors "SSF 0, 2, 3, 4, 5, and 6". Mann-Whitney test was applied among various categories and p value < 0.05 was considered significant. Three-step feature selection was performed to determine the best parameters among each category.

RESULTS

The best performing parameters were (1) THY vs TH- Mean at "SSF 0" (AUC: 0.8889) and MPP at "SSF 0" (AUC: 0.8889), (2) Low vs high WHO grade - no parameter showed statistical significance with good AUC, and (3) Low vs high MK/ITMIG stage- SD at "SSF 6" (AUC: 0.8052 and 0.8333 respectively]).

CONCLUSION

CTTA revealed several parameters with excellent diagnostic performance in differentiating thymoma from thymic hyperplasia and MK/ITMIG high vs low stages. CTTA could potentially serve as a non-invasive tool for this stratification.

ADVANCES IN KNOWLEDGE

This study has employed texture analysis, a novel radiomics method on DECT scans to determine the best performing parameter and their corresponding cut-off values to differentiate among the above-mentioned categories. These new parameters may help add another layer of confidence to non-invasively stratify and prognosticate patients accurately which was only previously possible with a biopsy.

Acute Angle of Multilobulated Contours Improves the Risk Classification of Thymomas

Background: Computed tomography plays an important role in the identification and characterization of thymomas. It has been mainly used during preoperative evaluation for clinical staging. However, the reliable prediction of histological risk types of thymomas based on CT imaging features requires further study. In this study, we developed and validated a nomogram based on CT imaging and included new indices for individualized preoperative prediction of the risk classification of thymomas. Methods: We conducted a retrospective, multicenter study that included 229 patients from two Chinese medical centers. All the patients underwent cross-sectional CT imaging within 2 weeks before surgery. The results of pathological assessments were retrieved from existing reports of the excised lesions. The tumor perimeter that contacted the lung (TPCL) was evaluated and a new quantitative indicator, the acute angle (AA) formed by adjacent lobulations, was measured. Two predictive models of risk classification were created using the least absolute shrinkage and selection operator (LASSO) method in a training cohort for features selection. The model with a smaller Akaike information criterion was then used to create an individualized imaging nomogram, which we evaluated regarding its prediction ability and clinical utility. Results: A new CT imaging-based model incorporating AA was developed and validated, which had improved predictive performance during risk classification of thymomas when compared with a model using traditional imaging predictors. The new imaging nomogram with AA demonstrated its clinical utility by decision curve analysis. Conclusions: Acute angle can improve the performance of a CT-based predictive model during the preoperative risk classification of thymomas and should be considered a new imaging marker for the evaluation and treatment of patients with thymomas. On the contrary, TPCL is not useful as a predictor for the risk classification of thymomas in this study.

Advancement in Diagnostic Imaging of Thymic Tumors

Thymic tumors are rare neoplasms even if they are the most common primary neoplasm of the anterior mediastinum. In the era of advanced imaging modalities, such as functional MRI, dual-energy CT, perfusion CT and radiomics, it is possible to improve characterization of thymic epithelial tumors and other mediastinal tumors, assessment of tumor invasion into adjacent structures and detection of secondary lymph nodes and metastases. This review aims to illustrate the actual state of the art in diagnostic imaging of thymic lesions, describing imaging findings of thymoma and differential diagnosis.

The role of thymectomy in myasthenia gravis: A programmatic approach to thymectomy and perioperative management of myasthenia gravis

BACKGROUND

Myasthenia gravis is a rare autoimmune disease caused by antibodies that probably originate from the thymus glands. This study examined the epidemiology of patients with MG, who underwent thymectomy over the last three decades.

METHODS

The objectives of this observational study were to investigate the clinicopathological features, treatment modalities, and prognostic factors for patients with thymic masses, over three decades at the Royal Hospital, Muscat, Oman.

RESULTS

There were 100 patients who underwent thymectomy with a mean (SD) age of 32.0 (8.6) years, of which 20% were men and 80% were women. Their follow up period, cardiac and neurology clinics, ranged from 1.5 to 12.0 years with a mean (SD) of 6.0 (3.0) years. Small percentage of MG patients had diabetes and hypertension and 10% of patients have positive family history of MG. Symptoms at the onset of the disease were ophthalmoplegia in 75%, limb weakness in 39%, bulbar symptoms in 57% and respiratory symptoms in 39% of patients. The Osserman grading was Grade I - 5%, Grade IIA - 39%, Grade IIB - 34%, and Grade III - 22%. Post thymectomy, 21% of patients had complete clinical remission, 76% of patients had significant clinical improvement and 3% had no apparent improvement in their clinical status. Histologically, hyperplasia was found in 57% and involuted thymus in 18% of patients.

CONCLUSION

Thymectomy can reduce patient's need for medication and reduce the severity of MG regardless of age, sex, severity, or length of sickness, or thymic masses. The early-onset, sever M.G, female, thymic hyperplasia benefit the most. Patients classified as Osserman Class IIA and IIB benefit most from this procedure.

CT imaging-based machine learning model: a potential modality for predicting low-risk and high-risk groups of thymoma: "Impact of surgical modality choice"

INTRODUCTION

Radiomics methods are used to analyze various medical images, including computed tomography (CT), magnetic resonance, and positron emission tomography to provide information regarding the diagnosis, patient outcome, tumor phenotype, and the gene-protein signatures of various diseases. In low-risk group, complete surgical resection is typically sufficient, whereas in high-risk thymoma, adjuvant therapy is usually required. Therefore, it is important to distinguish between both. This study evaluated the CT radiomics features of thymomas to discriminate between low- and high-risk thymoma groups.

MATERIALS AND METHODS

In total, 83 patients with thymoma were included in this study between 2004 and 2019. We used the Radcloud platform (Huiying Medical Technology Co., Ltd.) to manage the imaging and clinical data and perform the radiomics statistical analysis. The training and validation datasets were separated by a random method with a ratio of 2:8 and 502 random seeds. The histopathological diagnosis was noted from the pathology report.

RESULTS

Four machine-learning radiomics features were identified to differentiate a low-risk thymoma group from a high-risk thymoma group. The radiomics feature names were Energy, Zone Entropy, Long Run Low Gray Level Emphasis, and Large Dependence Low Gray Level Emphasis.

CONCLUSIONS

The results demonstrated that a machine-learning model and a multilayer perceptron classifier analysis can be used on CT images to predict low- and high-risk thymomas. This combination could be a useful preoperative method to determine the surgical approach for thymoma.

Added Value of Magnetic Resonance Imaging for the Evaluation of Mediastinal Lesions

The high soft tissue contrast and tissue characterization properties of magnetic resonance imaging allow further characterization of indeterminate mediastinal lesions on chest radiography and computed tomography, increasing diagnostic specificity, preventing unnecessary intervention, and guiding intervention or surgery when needed. The combination of its higher soft tissue contrast and ability to image dynamically during free breathing, without ionizing radiation exposure, allows more thorough and readily appreciable assessment of a lesion's invasiveness and assessment of phrenic nerve involvement, with significant implications for prognostic clinical staging and surgical management.

Thymic Epithelial Neoplasms: Radiologic-Pathologic Correlation

Thymic epithelial neoplasms, as classified by the World Health Organization, include thymoma, thymic carcinoma, and thymic carcinoid. They are a rare group of tumors and are often diagnosed incidentally in the work-up of parathymic syndrome, such as myasthenia gravis, or when mass effect or local invasion causes other symptoms. In each of these scenarios, understanding the radiologic-pathologic relationship of these tumors allows clinical imagers to contribute meaningfully to management decisions and overall patient care. Integrating important imaging features, such as local invasion, and pathologic features, such as necrosis and immunohistochemistry, ensures a meaningful contribution by clinical imagers to the care team.

Development and validation of a CT-texture analysis nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes

BACKGROUND

Thymic epithelial tumors (TETs) are the most common primary tumors in the anterior mediastinum, which have considerable histologic heterogeneity. This study aimed to develop and validate a nomogram based on computed tomography (CT) and texture analysis (TA) for preoperatively predicting the pathological classifications for TET patients.

METHODS

Totally TET 172 patients confirmed by postoperative pathology between January 2011 to April 2019 were retrospectively analyzed and randomly divided into training (n = 120) and validation (n = 52) cohorts. Preoperative clinical factors, CT signs and texture features of each patient were analyzed, and prediction models were developed using the least absolute shrinkage and selection operator (LASSO) regression. The performance of the models was evaluated and compared by the area under receiver-operator characteristic (ROC) curve (AUC) and the DeLong test. The clinical application value of the models was determined via the decision curve analysis (DCA). Then, a nomogram was developed based on the model with the best predictive efficiency and clinical utility and validated using the calibration plots.

RESULTS

Totally 87 patients with low-risk TET (LTET) (types A, AB, B1) and 85 patients with high-risk TET (HTET) (types B2, B3, C) were enrolled in this study. We separately constructed 4 prediction models for differentiating LTET from HTET using clinical, CT, texture features, and their combination. These 4 prediction models achieved AUCs of 0.66, 0.79, 0.82, 0.88 in the training cohort and 0.64, 0.82, 0.86, 0.94 in the validation cohort, respectively. The DeLong test and DCA showed that the Combined model, consisting of 2 CT signs and 2 texture parameters, held the highest predictive efficiency and clinical utility (p < 0.05). A prediction nomogram was subsequently developed using the 4 independently risk factors from the Combined model. The calibration curves indicated a good consistency between the actual observations and nomogram predictions for differentiating TET classifications.

CONCLUSION

A prediction nomogram incorporating both the CT and texture parameters was constructed and validated in our study, which can be conveniently used for the preoperative individualized prediction of the simplified histologic subtypes in TET patients.

A single-center experience: management of patients with thymic epithelial tumors

Background

Thymic epithelial tumors are rare neoplasias. There are no internationally accepted standards to treat this complex oncological disease. The studies on which our knowledge is based frequently have methodological weaknesses. If the tumor is resectable, complete surgical excision is currently the first-line therapy. Thymic epithelial tumors respond to radiation. The therapeutic benefit of adjuvant radiotherapy depends on tumor stage. To validate and improve treatment, we share our current experiences with clinical management and surgical intervention.

Methods

This single-center retrospective study included 40 patients with primarily resectable thymic epithelial tumors who underwent resection with curative intent. The survival data was collected and presented according to Kaplan-Meier. Single- and multiple predictor survival analyses were carried out using the log-rank test and Cox proportional hazards model.

Results

Single-predictor survival analysis showed survival to be dependent on the Masaoka-Koga classification, WHO histological classification, resection status, surgical technique, and Clavien-Dindo grade for postoperative complications. Multiple predictor analysis confirms that the Masaoka-Koga stage (HR = 4.876, P = 0.032) and Clavien-Dindo grade (HR = 4.904, P = 0.011) are independent prognostic factors for survival.

Conclusion

In addition to the Masaoka stage, the occurrence of severe postoperative complications represents an independent prognostic factor. Given the tumor’s sensitivity to radiation, the use of neoadjuvant radiotherapy can be considered to downstage Masaoka-Koga stages III and higher, thus reducing surgical risks. Further prospective multicenter studies are urgently needed.

Value of metabolic parameters in distinguishing primary mediastinal lymphomas from thymic epithelial tumors

Objective: A high rate of unnecessary thymectomies has been reported. This study aimed to distinguish primary mediastinal lymphomas (PMLs) from thymic epithelial tumors (TETs) by evaluating volumetric and metabolic parameters with ¹⁸F-FDG PET/CT.

Methods: A total of 136 patients who were pathologically diagnosed with TETs or PMLs were enrolled, and ¹⁸F-FDG PET/CT was performed before therapy. Volumetric parameters, including the mean SUV (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and SUVmax, were determined and compared between the 2 subtypes. The diagnostic performance of these parameters was evaluated with receiver operating characteristic (ROC) curve analysis.

Results: All parameters significantly differed between patients with PMLs and TETs. Patients with lymphomas were younger and had higher SUVmean, SUVmax, TLG, and MTV values than patients with TETs. The MTV and TLG values had similar diagnostic performance. ROC analysis indicated that the areas under the curves of the SUVmean and SUVmax values performed similarly (approximately 0.76) in differentiating patients with PMLs from TETs, and both values were better than the MTV and TLG values. When age was included with the SUVmax in differentiating TETs from PMLs, the AUC was 0.91, and the sensitivity and specificity increased to 80% and 93%, respectively.

Conclusions: The SUVmax and volumetric parameters of ¹⁸F-FDG PET/CT can be used to distinguish patients with PMLs versus TETs, and thus may aid in preventing unnecessary thymectomies or other invasive operations.

Uncommon thoracic manifestations from extrapulmonary tumors: Computed tomography evaluation - Pictorial review

Although metastasis can occur at a variety of sites, pulmonary involvement is common in patients with cancer. Depending on the source and type of tumor, pulmonary metastases present with a wide range of radiologic appearances. Hematogenous dissemination through the pulmonary arteries to the pulmonary capillary network is the most common form of spread in pulmonary metastases. However, they may also reach the lung via lymphatic dissemination, secondary airway involvement, vessel tumor embolism, and direct chest invasion. In the evaluation of patients with known extrathoracic tumors, CT is the state-of-the-art imaging modality for detecting and characterize pulmonary metastases as well as to predict resectability. Although CT limitations are well known, knowledge of growth rates of various tumors and understanding the pattern of spread may be helpful clues in suggesting and even establish the specific diagnosis. The purpose of this pictorial review is to discuss the imaging appearances of different patterns of intrathoracic tumoral dissemination.

Dual-energy CT perfusion imaging for differentiating WHO subtypes of thymic epithelial tumors

To evaluate the role of conventional contrast-enhanced CT (CECT) imaging and dual-energy spectral CT (DECT) perfusion imaging in differentiating the WHO histological subtypes of thymic epithelial tumours (TETs). Eighty-eight patients with TETs who underwent DECT perfusion scans (n = 51) and conventional CT enhancement scans (n = 37) using a GE Discovery CT750 HD scanner were enrolled in this study. The mean maximal contrast-enhanced range (mean CEmax) and the perfusion and spectral parameters of the lesions were analysed. Among the six WHO subtypes (Type A, AB, B1, B2, and B3 thymoma and thymic carcinoma), the mean CEmax values and most of the perfusion and spectral parameter values of Type A and Type AB were significantly higher than those of the other subtypes (all P < 0.05), and there was no difference among Type B1, B2 and B3 (all P > 0.05). The mean CEmax value was not different between Type B (including Type B1, B2, and B3) and thymic carcinoma (P = 1.000). The PS, IC, NIC and λHU values in the optimal venous phase of thymic carcinoma were higher than those of Type B (all P < 0.05). The parameters of conventional CECT imaging and DECT perfusion imaging can help identify the subtype of TETs, especially those of DECT perfusion imaging in type B thymomas and thymic carcinomas.

Magnetic Resonance Imaging for the Follow-up of Treated Thymic Epithelial Malignancies

PURPOSE

The purpose of this article was to compare magnetic resonance imaging (MRI) depiction of thymic malignancy progression/recurrence with that of computed tomography (CT).

METHODS

We retrospectively reviewed all surgically treated thymic epithelial malignancy (TEM) patients between 2011 and 2018 who were followed-up with chest CT and MRI. We compared the detection of recurrence and metastatic disease between the CT and MRI scans in each of these patients.

RESULTS

Of 187 patients treated in our institution for TEM, 22 were followed-up with both CT and MRI. TNM stage at diagnosis was as follows: I (n=14), II (n=1), IIIa (n=4), IIIb (n=2), IVa (n=1), and IVb (n=0). Patients were followed-up for a mean of 6.2 years, range 0.7 to 17.7 years. The mean interval between CT and MRI was 5.4 (range, 1 to 15) months. Most patients had no recurrence (n=16), 4 had recurrence after R0 or R1 resection, 1 had stable disease, and 1 had progression of disease after R2 resection. CT and MRI performed equally in the identification of pleural spread (n=5), lymphadenopathy (n=4), and pulmonary metastases (n=1). Retrosternal recurrence (n=1) was identified by MRI despite sternotomy wire artifacts. MRI identified bone involvement and extension of disease into the thecal sac earlier and more readily. Three patients had an indeterminate mediastinal finding on CT that was correctly identified as a benign cyst or pericardial fluid collection by MRI.

CONCLUSION

MRI is an alternative option to follow-up patients after treatment for TEM. However, for those with metallic sternotomy wires, we recommend alternating the follow-up with CT as well.

A radiomics model to predict the invasiveness of thymic epithelial tumors based on contrast‑enhanced computed tomography

In the present study, we aimed to construct a radiomics model using contrast‑enhanced computed tomography (CT) to predict the pathological invasiveness of thymic epithelial tumors (TETs). We retrospectively reviewed the records of 179 consecutive patients (89 females) with histologically confirmed TETs from two hospitals. The 82 low‑ and 97 high‑risk TETs were assigned to training (90 tumors), internal validation (49 tumors) and external validation (40 tumors) cohorts. Radiomics features extracted from preoperative contrast‑enhanced chest CT were selected using least absolute shrinkage and selection operator logistic regression. Three prediction models were developed using multivariate logistic regression analysis. Their performance and clinical utility were assessed using receiver operating characteristic curves and the DeLong test, respectively. Eight radiomics features with non‑zero coefficients were used to develop a radiomics score, which significantly differed between low‑ and high‑risk TETs (P<0.001). The subjective finding, infiltration, was independently associated with high‑risk TETs. Prediction models based on infiltration alone, the radiomics signature alone, and both these parameters showed diagnostic accuracies of 72.2% [area under curve (AUC), 0.731; 95% confidence interval (CI): 0.627‑0.819; sensitivity, 85.7%; specificity, 60.4%], 88.9% (AUC, 0.944; 95% CI: 0.874‑0.981; sensitivity, 92.9%; specificity, 85.4%), and 90.0% (AUC, 0.953; 95% CI: 0.887‑0.987; sensitivity, 92.9%; specificity, 87.5%), respectively. Decision‑curve analysis showed that the combined model added more net benefit than the single‑parameter models. In conclusion, a radiomics signature based on contrast‑enhanced CT has the potential to differentiate between low‑ and high‑risk TETs. The model incorporating the radiomics signature and subjective finding may facilitate the individualized, preoperative prediction of the pathological invasiveness of TETs.

Evaluation of surgical procedures in primary mediastinal cysts and tumors: single-center experience

Aim

In this study, we aimed to evaluate the results of our patients with a primary mediastinal mass and the surgical techniques applied in our clinic retrospectively.

Material and methods

Between March 2015 and March 2019, the results and treatment protocols of 32 patients with a primary mediastinal mass or cysts who were followed up and treated in our clinic were evaluated retrospectively. Twenty-six patients who underwent surgery for biopsy or resection were included in the study.

Results

Sixteen of our patients were male and 10 were female. The mean age was 39 years. 80.2% of our patients were symptomatic and 19.2% were asymptomatic and a mediastinal mass was incidentally detected in these asymptomatic patients. The most common symptom was dyspnea with frequency of 38.4%. In terms of localization, the mass was lateralized on the right side in 7 patients, on the left side in 5 patients. In 13 patients, the tumor was located in the posterior mediastinum. 8 patients underwent anterior mediastinotomy and 1 patient underwent biopsy with video-assisted thoracoscopic surgery (VATS). Most commonly a thymus-derived mass was seen. Fifteen patients underwent excision with VATS, 3 thoracotomy, 2 sternotomy and in 1 patient VATS assisted anterior minithoracotomy was performed.

Conclusions

Mediastinal tumors and cysts have different histopathological features. Robotic surgery and VATS-assisted surgery are increasingly used in surgical excision.

Relationship Between Computed Tomography Imaging Features and Clinical Characteristics, Masaoka-Koga Stages, and World Health Organization Histological Classifications of Thymoma

Objectives: Computed tomography (CT) is an important technique for evaluating the condition and prognosis of patients with thymomas, and it provides guidance regarding treatment strategies. However, the correlation between CT imaging features, described using standard report terms, and clinical characteristics, Masaoka-Koga stages, and World Health Organization (WHO) classifications of patients with thymomas has not been described in detail nor has risk factor analysis been conducted. Methods: Overall, 159 patients with thymomas who underwent preoperative contrast-enhanced CT between September 2011 and December 2018 were retrospectively reviewed. We assessed the clinical information, CT imaging features, and pathological findings for each patient. A total of 89 patients were specially used to evaluate postoperative recurrence or metastasis between September 2011 and December 2015 to obtain an appropriate observation period. The relationship between CT imaging features and clinical characteristics, Masaoka-Koga stage, and WHO histological classification were analyzed, and related risk factors based on CT imaging features were identified. Results: CT imaging features did not significantly differ based on sex or age. Some imaging features demonstrated significant differences between the groups with and without related clinical characteristics. Contour (odds ratio [OR] = 3.711, P = 0.005), abutment ≥50% (OR = 4.277, P = 0.02), and adjacent lung abnormalities (OR = 3.916 P = 0.031) were independent risk factors for relapse or metastasis. Among all imaging features, there were significant differences between stage I/II and III/IV lesions in tumor size, calcification, infiltration of surrounding fat, vascular invasion, pleural nodules, elevated hemidiaphragm, and pulmonary nodules. Tumor size (odds ratio = 1.261, P = 0.014), vascular invasion (OR = 2.526, P = 0.023), pleural nodules (OR = 2.22, P = 0.048), and pulmonary nodules (OR = 3.106, P = 0.006) were identified as independent risk factors. Tumor size, contour, internal density, infiltration of surrounding fat, and pleural effusion significantly differed between low- and high-risk thymomas. Tumor size (OR = 1.183, P = 0.048), contour (OR = 2.288, P = 0.003), internal density (OR = 2.192, P = 0.024), and infiltration of surrounding fat (OR = 2.811 P = 0.005) were independent risk factors. Conclusions: Some CT imaging features demonstrated significant correlations with clinical characteristics, Masaoka-Koga clinical stages, and WHO histological classifications in patients with thymomas. Familiarity with CT features identified as independent risk factors for these related clinical characteristics can facilitate preoperative evaluation and treatment management for the patients with thymoma.

Update in diagnostic imaging of the thymus and anterior mediastinal masses

Anterior mediastinal masses include a wide spectrum of malignant and benign pathologies with a large percentage represented by thymic lesions. Distinguishing these masses on diagnostic imaging is fundamental to guide the proper management for each patient. This review illustrates possibilities and limits of different imaging modalities to diagnose a lesion of the anterior mediastinum with particular attention to thymic disease.

Comparison between CT and MRI in the Diagnostic Accuracy of Thymic Masses

Purpose: The aim of this study was to compare diagnostic accuracy between CT and MRI for thymic masses.

Methods: We searched literature and collected information on first author, publication year, cases of different types of thymic lesions, correct diagnostic cases of CT and MRI and results of quantitative analysis of CT and MRI. The ROC curve was applied to compare the diagnostic performance of different imaging modalities.

Results: Eight literatures were finally included and analyzed in this study. There were 253 cases examined by CT and 340 cases by MRI in total. We showed outcomes of quantitative analysis of each study in this article. The sensitivity of CT and MRI was both 100%, while the specificity was 75% and 80%, respectively. AUC of CT was 0.875 [95%CI: 0.473, 0.997] and that of MRI was 0.880 [95%CI: 0.531, 0.995].

Conclusion: The diagnostic accuracy of MRI is superior to CT in detecting thymomas, thymic cysts or thymic hyperplasia but that of CT and MRI is still unclear in differentiating thymic carcinomas and lymphomas/germ cell tumors.

Stage-related outcome for thymic epithelial tumours

BACKGROUND

Thymic epithelial tumours (TETs) are characterized by a wide variety of biological behaviors. Radical resection and stage are strong prognostic factors. Aim of this study is to review our Single Center Experience.

METHODS

One hundred and seventy-seven patients observed in the period from January 2000 to December 2016 were included in the study. Data regarding clinicopathologic features, treatment, and survival were collected. Stage-related clinical standpoints and therapeutic options were also evaluated.

RESULTS

Non-surgical treatment was primarily performed in 15 (8.47%), unresectable disease was intraoperatively found in 12 cases (7.4%). The analysis of 150 patients undergoing curative surgery revealed 70 stage I TET (46.66%), 49 stage II (32.66%), 19 stage III (12.66%), 6 stage IVa (4%) and 6 stage IVb (4%) at the first hospital admission. Histology identified 12 A thymoma (8%), 38 AB (25.33%), 24 B1 (16%), 50 B2 (33.33%), 19 B3 (12.66%) and 7 carcinomas (4.66%). The mean follow up time was 84.14 months (sd = 61.68 months). Disease relapse occurred in 13 patients (8.78%) at a mean period of 78.85 months (sd = 60.87 months) after surgery. Exitus due to thymoma happened in 6 cases (4.05%) after a mean survival of 56.02 months (sd = 25.17 months). The 5-year overall survival rate was 0.94 (95%CI 0.88-0.97) and the 5-year disease-free survival rate was 0.90 (95%CI 0.83-0.94). The 5-year overall survival rates were 96.1% (95% CI, 89.9-98.5%) for the early stages and 87.4% (95% CI, 65.6-95.8%) for the advanced stages (p = 0.670). The 5-year disease-free survival rates resulted being 98.8% (95% CI, 92.3-99.8%) for the early stages and 59.8% (95% CI, 37.8-76.2%) for the advanced stages (p < 0.001).

CONCLUSIONS

Advanced stage TETs are characterized by higher mortality and recurrence rates. Although technically demanding, surgery, as part of multimodality therapy, could prolong survival. Iterative surgical treatment of recurrences is a viable option for selected patients.

TRIAL REGISTRATION

The study was approved by the Institutional Review Board of Perugia and Terni University Hospitals [Code T1003] and was retrospectively registered.

Multilobulated thymoma with an acute angle: a new predictor of lung invasion

OBJECTIVE

Imaging features of thymomas such as lobulation, infiltration into lung, and adjacent lung abnormality have been associated with lung invasion but are unreliable. The goal of this study was to develop a more objective and reproducible method for predicting lung invasion by thymomas.

SUBJECTS AND METHODS

Fifty-four thymomas resected from 2007 to 2017 were included for analysis. Pre-operative CT scans for these thymomas were reviewed, and multiple features were evaluated, including the interface of each thymoma with the adjacent lung. A multilobulated thymoma with at least one acute angle between lobulations was considered suspicious for lung invasion. Two blinded radiologists then tested this hypothesis by reviewing all 54 CT scans and using this single criterion to predict lung invasion.

RESULTS

Twelve thymomas invaded the lung. All lung-invasive thymomas were multilobulated. Twenty-nine thymomas had a multilobulated interface with the lung. Multilobulated thymomas were more likely to invade the lung than thymomas with a single lobulation or no lobulation (p = 0.0008). Using the criterion of multilobulation with at least one acute angle between lobulations to predict lung invasion, the two readers achieved a sensitivity of 67-83%, specificity of 93-98%, positive predictive value of 77-89%, and negative predicted value of 91-95%. Nine lung-invasive thymomas also invaded mediastinal structures or disseminated to the pleura.

CONCLUSIONS

A multilobulated thymoma with at least one acute angle between lobulations predicts lung invasion with a high degree of accuracy. When lung invasion is suspected, the findings are indicative of a locally aggressive tumor, and the pleura and mediastinal structures should also be closely inspected for invasion.

KEY POINTS

• A multilobulated thymoma with at least one acute angle between lobulations is predictive of lung invasion. • Coronal and sagittal reformations and thin sections are helpful in challenging cases. • Lung invasion indicates a locally aggressive tumor, and the pleura and other mediastinal structures should also be closely inspected for invasion.

Mediastinal and Pleural MR Imaging: Practical Approach for Daily Practice

Radiologists in any practice setting should be prepared to use thoracic magnetic resonance (MR) imaging for noncardiac and nonangiographic applications. This begins with understanding the sequence building blocks that can be used to design effective thoracic MR imaging protocols. In most instances, the sequences used in thoracic MR imaging are adapted from protocols used elsewhere in the body. Some modifications, including the addition of electrocardiographic gating or respiratory triggering, may be necessary for certain applications. Once protocols are in place, recognition of clinical scenarios in which thoracic MR imaging can provide value beyond other imaging modalities is essential. MR imaging is particularly beneficial in evaluating for benign features in indeterminate lesions. In lesions that are suspected to be composed of fluid, including mediastinal cysts and lesions composed of dilated lymphatics, MR imaging can confirm the presence of fluid and absence of suspicious enhancement. It can also be used to evaluate for intravoxel lipid, a finding seen in benign residual thymic tissue and thymic hyperplasia. Because of its excellent contrast resolution and potential for subtraction images, MR imaging can interrogate local treatment sites for the development of recurrent tumor on a background of post-treatment changes. In addition to characterization of lesions, thoracic MR imaging can be useful in surgical and treatment planning. By identifying nodular sites of enhancement or areas of diffusion restriction within cystic or necrotic lesions, MR imaging can be used to direct sites for biopsy. MR imaging can help evaluate for local tumor invasion with the application of "real-time" cine sequences to determine whether a lesion is adherent to an adjacent structure or surface. Finally, MR imaging is the modality of choice for imaging potential tumor thrombus. By understanding the role of MR imaging in these clinical scenarios, radiologists can increase the use of thoracic MR imaging for the benefit of improved decision making in the care of patients. ^©RSNA, 2018.

Multislice computed tomography performance in differential diagnosis of high-density thymic cyst and thymoma in lesions less than 3 cm

Background

This study was conducted to evaluate the performance of multislice computed tomography (MSCT) to diagnose high‐density thymic cysts and thymomas in lesions measuring < 3 cm.

Methods

The records of 42 patients admitted to Ningbo No. 2 Hospital with an anterior mediastinal mass (diameter < 3 cm) suspected of carcinoma originating from the thymus were retrospectively analyzed. All patients underwent surgery and pathological examination. Twenty‐eight were diagnosed with thymic cysts and 14 with thymoma. The features of thymic cysts and thymomas revealed on MSCT were compared.

Results

Mediastinal masses with a triangular or teardrop shape and a straight mediastina–lung border were more likely to be diagnosed as thymic cysts (P < 0.05), while those with a bulging nodule–lung border were more likely thymomas (P < 0.05). Using the CT value as a reference for differential diagnosis, the diagnostic sensitivity, specificity, and area under the receiver operating characteristic curve for CT values of non‐contrast CT images, enhanced CT values, and ΔCT values were 0.65 (0.47–0.84), 0.95(0.86–1.00), and 0.96 (0.89–1.00), respectively.

Conclusion

MSCT of high‐density thymus gland nodules (maximum diameter ≤ 3 cm) can reveal specific features that could be helpful for differential diagnosis.

Intravoxel incoherent motion diffusion-weighted MR imaging parameters predict pathological classification in thymic epithelial tumors

We evaluated the performance of intravoxel incoherent motion (IVIM) parameters for preoperatively predicting the subtype and Masaoka stage of thymic epithelial tumors (TETs). Seventy-seven patients with pathologically confirmed TETs underwent a diffusion weighted imaging (DWI) sequence with 9 b values. Differences in the slow diffusion coefficient (D), fast perfusion coefficient (D), and perfusion fraction (f) IVIM parameters, as well as the multi b-value fitted apparent diffusion coefficient (ADC_mb), were compared among patients with low-risk (LRT) and high-risk thymomas (HRT) and thymic carcinomas (TC), and between early stage (stages I and II) and advanced stage (stages III and IV) TET patients. ADC_mb, D, and D values were higher in the LRT group than in the HRT or TC group, but did not differ between the HRT and TC groups. The mean ADC_mb, D, and D values were higher in the early stage TETs group than the advanced stage TETs group. The f values did not differ among the groups. These results suggest that IVIM DWI could be used to preoperatively predict subtype and Masaoka stage in TET patients.

Volumetric Modulated Arc (Radio) Therapy in Pets Treatment: The "La Cittadina Fondazione" Experience

Volumetric Modulated Arc Therapy (VMAT) is a modern technique, widely used in human radiotherapy, which allows a high dose to be delivered to tumor volumes and low doses to the surrounding organs at risk (OAR). Veterinary clinics takes advantage of this feature due to the small target volumes and distances between the target and the OAR. Sparing the OAR permits dose escalation, and hypofractionation regimens reduce the number of treatment sessions with a simpler manageability in the veterinary field. Multimodal volumes definition is mandatory for the small volumes involved and a positioning device precisely reproducible with a setup confirmation is needed before each session for avoiding missing the target. Additionally, the elaborate treatment plan must pursue hard constraints and objectives, and its feasibility must be evaluated with a per patient quality control. The aim of this work is to report results with regard to brain meningiomas and gliomas, trigeminal nerve tumors, brachial plexus tumors, adrenal tumors with vascular invasion and rabbit thymomas, in comparison with literature to determine if VMAT is a safe and viable alternative to surgery or chemotherapy alone, or as an adjuvant therapy in pets.

Evaluation of anterior mediastinal solid tumors by CT perfusion: a preliminary study

PURPOSE

We aimed to assess the role of computed tomography (CT) perfusion in differentiation of thymoma from thymic hyperplasia, lymphoma, thymic carcinoma, and lung cancer invading anterior mediastinum.

METHODS

In this study, 25 patients with an anterior mediastinal lesion underwent CT perfusion imaging from January 2015 to February 2016. Diagnoses included thymoma (n=7), thymic hyperplasia (n=8), lymphoma (n=4), thymic carcinoma (n=3), and invasive lung cancer (n=3). Lymphoma, thymic carcinoma, and lung cancer were grouped as malignant tumors for statistical analysis. Values for blood flow, blood volume, and permeability surface were measured in CT perfusion.

RESULTS

Blood flow and blood volume values were higher in thymoma in comparison to thymic hyperplasia; however, the difference was not statistically significant. Blood volume values were significantly higher in thymoma (mean, 11.4 mL/100 mL; range, 5.2-20.2 mL/100 mL) compared with lymphoma (mean, 5.3 mL/100 mL; range, 2.5-7.2 mL/100 mL) (P = 0.023). Blood flow and blood volume values were significantly higher in thymoma compared with non-thymoma malignant tumors (P = 0.025).

CONCLUSION

CT perfusion is helpful in differentiating thymoma from non-thymoma malignancies including lymphoma, thymic carcinoma, and invasive lung cancer involving the anterior mediastinum.

Doubling time of thymic epithelial tumours on CT: correlation with histological subtype

OBJECTIVES

We retrospectively evaluated the doubling time (DT) of thymic epithelial tumours (TET) according to the histological subtype on CT.

METHODS

From January 2005 to June 2016, we enrolled 53 patients who had pathologically confirmed TET and at least two CT scans. Tumour size was measured using a two-dimensional method, and the DT was calculated. DTs were compared among histological subtypes, and factors associated with rapid tumour growth (DT <180 days) were assessed.

RESULTS

In 42 of the 53 patients (79.2%) the tumours showed interval growth (>2 mm) during follow-up. The median DT for all tumours was 400 days (range 48-1,964 days). There were no significant differences in DT in relation to histological subtype (p = 0.177). When TETs were recategorized into three groups, i.e. low-risk thymomas (types A, AB, B1), high-risk thymomas (types B2, B3), and thymic carcinoma, DT was significantly different among the groups (median DT 436, 381 and 189 days, respectively; p = 0.031). Histological subtype (type B3 and thymic carcinoma) was the single independent predictor of rapid tumour growth.

CONCLUSIONS

The majority of TETs grew during follow-up with variable and relatively slow growth rates. Histological features of aggressive behaviour significantly correlated with a decreased DT and rapid growth.

KEY POINTS

• The majority of thymic epithelial tumours grew during follow-up (79.2%, 42/53). • Doubling times of thymic epithelial tumours were highly variable (median 400 days). • Histological features of aggressive behaviour significantly correlated with a decreased doubling time.